Sub-prime Translation service Model

A week back, our Bengali team received a 12,00 words translation to be reviewed. The client said that they were going to do DTP and we need to hurry. There were some 15 files and we opened them.

What did we see ?

We found application of an innovation / idea that revolution telecom and then made banking almost at the brink of collapse.

The process is : Sampling, Coding, Multiplexing and Adaptive Prediction.

The Translation

The files were a mixture of human and machine translation and machine translation poorly edited. More important, the whole 12,500 words were cut into sample sizes of 500-600 words and then the process of a) human translation of HT b)machine translation or MT c) edited machine translation EMT – applied. The end product was a random mixture of HT packets, MT packets and EMT packets, each packet size some 500-600 words – somewhat the length of this post.

Now, unless the translation goes through a very rigorous check, there is a fair chance that the translation may get through with no alert flag ( this probability is 1/3 or 33.3%). The reviewer may check 2 three segments and they may be HT and EMT which will not warrant any alarm.

This ‘innovation’ will work wonder for everyone down the chain – 50-60% cost reduction, 70% reduction in turn around time and everyone is happy.

As long as our presumption of the MT (other 33% of probability) not manifesting, the translation will go around and multiple parties can trade on them and multiple parties ‘owning’ chunks of it.

Detection

Now suppose at some unlucky moment, a series of MT chunks (toxic translation) started surfacing in various ends and choking meaning everywhere. Now, since the packets have spread through many TMs, databases, end-translations as the case may be and the best treatment is to reject all but that also means end of the industry at that moment. The accountability also got spread and granulated and then end client needs to get a fresh translation.

Sub-prime Housing Loan crisis was more of less like this. A box full of loans were sampled and cut into smaller pieces and then re-packed with some marker – prime, sub-prime, etc. Then these got mixed up and started to enter the financial mainstream. Things were OK as long as there was not considerable detection.

As soon as toxic chunks started to be detected, the system went into unstable mode and finally, taxpayers bailed it out.